The purpose of this research is to measure risk in common stocks in Korean financial firms by industrial clusters applying a nonparametric methodology, which is Monte Carlo simulation, but also to identify the most critical factor explaining the volatility of stocks in financial firms and in each sector of financial firms (banks, insurance companies, and investment and security trading companies). The study suggests that the stock returns of Korean firms are covariated because of this parallel shift factor. The result shows similar VaRs and ESs for each industry when using a factor analytic approach.
목차
Abstract 1. Introduction 2. Measuring Risk 3. Monte Carlo Simulation 3.1 Scenario Generation 3.2 Decomposition 3.3 Covariance Estimation by PCA 3.4 Building Asset Price Simulator 4. Empirical Test 4.1 Data and Summary Statistics 4.2 Analysis of Principal Factors 5. Conclusion References Table Figure
키워드
Risk managementValue at RiskExpected ShortfallFull valuationMonte Carlo simulationPrincipal Component AnalysisIto’s lemmaNonparametric method
저자
Seungho Baek [ Stuart School of Business, Illinois Institute of Technology ]
Joseph D. Cursio [ Stuart School of Business, Illinois Institute of Technology ]
Seung Youn Cha [ College of Business, Seoul National University ]
Corresponding Author